Quantum Intelligence for Humanity: The Quantum Biomedical Discovery Engine
Abstract
Modern medicine possesses extraordinary volumes of biological and clinical knowledge, yet discovery remains constrained by fragmented data, slow experimental cycles, and weak translation between computational insight and patient benefit. This concept paper proposes the Quantum Biomedical Discovery Engine (QBDE): a human-centered research architecture integrating advanced artificial intelligence, selectively useful quantum computation, automated laboratories, patient-specific digital models, and independent clinical validation within a governed learning loop. The framework assigns quantum processors only to bounded tasks that demonstrate auditable advantage over strong classical methods. It requires prospective laboratory replication, clinical evidence, explicit human authority, cybersecurity, biosecurity, privacy protection, equitable access, and transparent stop rules. Applications include oncology, infectious disease, rare disease, neurodegeneration, healthy longevity, advanced materials, energy, environmental science, infrastructure, cryptography, and fundamental research. The central proposition is that quantum intelligence should be judged not by computational spectacle, but by its capacity to generate safer, faster, more equitable, and more reliable knowledge.
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
- Stable adiabatic quantum batteries
- A novel self-lipid antigen targets human T cells against CD1c(+) leukemias
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.